|

The Attention Network Test: A potential tool to investigate the impact of health status on safe driving

Author(s): Michel Bédard

Slidedeck Presentation Only (no paper submitted):

2B - Bedard

Abstract:

Background/Context:

The safety of older drivers is an important social and health issue. Driving is a complex multi-factorial task that taps underlying mechanisms of cognition and attention. Age is often associated with declines in cognition and attention, and health conditions can exacerbate these natural changes. Many tests of cognition and attention are associated with driving outcomes, albeit not strongly. While it is becoming increasingly evident that no test of cognition or attention will be highly accurate in determining fitness-to-drive on its own, better understanding the contribution of cognition and attention to safe driving in older adults would still be beneficial. One test that has not been studied in-depth in the context of driving is the Attention Network Test (ANT). The ANT is based on the Human Attention Network model, which links specific neuro-anatomical structures and brain neurotransmitters to specific attention mechanisms. Therefore, examining ANT performance in the presence of various health conditions may provide insight into health-related changes that affect safe driving. However, one important first step is to verify that the ANT is not redundant with other tools of cognition and attention typically used for driving research and evaluation.

Aims/Objectives:

The major aim of this study was to determine the level of redundancy between the ANT and tests of cognition and attention used in the Candrive longitudinal study.

Methods/Target Group:

The ANT was added to four of the seven Candrive sites (Ottawa, Toronto, Thunder Bay, Victoria) during the third year of data collection. Scores on tests of cognition and attention from 451 older drivers were analysed to determine the strength of the associations between the ANT, and the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Motor-free Visual Perception Test (MVPT-3), the DemTect, the Screen for the Identification of Cognitively Impaired Medically At-Risk Drivers, A Modification of the DemTect (SIMARD-MD), and Trail Making Test parts A and B (TMT-A and B). We used correlations and multi-variable linear regression models to determine the level of relationship between ANT scores and scores on the other tests.
Results/Activities: The ANT was weakly correlated with nearly every test examined (r = .07 to .32). Using multi-variable linear regression, less than 10% of the variance in ANT scores was explained by scores on other tests of cognition, and most of the explained variance was related to tests of visual-cognitive abilities (MVPT-3, and TMT-A and B).

Discussion/Deliverables:

These findings indicate that the ANT is not redundant with other tests of cognition and that scores on the ANT may be explained by cognitive and attention processes that differ from those scrutinized by the other tests commonly used in driving research.

Conclusions:

The theoretical basis underpinning the Human Attention Network, in addition to the additional information that ANT scores may convey over and above other tests of cognition and attention, justify its further study. The exploration of associations between scores on the ANT and health conditions may lead to a better understanding of the impact of health status on safe driving.